7,712 research outputs found
Focal Spot, Spring/Summer 1985
https://digitalcommons.wustl.edu/focal_spot_archives/1040/thumbnail.jp
An automated workflow for parallel processing of large multiview SPIM recordings
Multiview light sheet fluorescence microscopy (LSFM) allows to image
developing organisms in 3D at unprecedented temporal resolution over long
periods of time. The resulting massive amounts of raw image data requires
extensive processing interactively via dedicated graphical user interface (GUI)
applications. The consecutive processing steps can be easily automated and the
individual time points can be processed independently, which lends itself to
trivial parallelization on a high performance cluster (HPC). Here we introduce
an automated workflow for processing large multiview, multi-channel,
multi-illumination time-lapse LSFM data on a single workstation or in parallel
on a HPC. The pipeline relies on snakemake to resolve dependencies among
consecutive processing steps and can be easily adapted to any cluster
environment for processing LSFM data in a fraction of the time required to
collect it.Comment: 13 pages with supplement, LATEX; 1 table, 1 figure, 2 supplementary
figures, 2 supplementary lists, 2 supplementary tables; corrected error in
results table, results unchange
Grid Databases for Shared Image Analysis in the MammoGrid Project
The MammoGrid project aims to prove that Grid infrastructures can be used for
collaborative clinical analysis of database-resident but geographically
distributed medical images. This requires: a) the provision of a
clinician-facing front-end workstation and b) the ability to service real-world
clinician queries across a distributed and federated database. The MammoGrid
project will prove the viability of the Grid by harnessing its power to enable
radiologists from geographically dispersed hospitals to share standardized
mammograms, to compare diagnoses (with and without computer aided detection of
tumours) and to perform sophisticated epidemiological studies across national
boundaries. This paper outlines the approach taken in MammoGrid to seamlessly
connect radiologist workstations across a Grid using an "information
infrastructure" and a DICOM-compliant object model residing in multiple
distributed data stores in Italy and the UKComment: 10 pages, 5 figure
MRI analysis for Hippocampus segmentation on a distributed infrastructure
Medical image computing raises new challenges due to the scale and the complexity of the required analyses. Medical image databases are currently available to supply clinical diagnosis. For instance, it is possible to provide diagnostic information based on an imaging biomarker comparing a single case to the reference group (controls or patients with disease). At the same time many sophisticated and computationally intensive algorithms have been implemented to extract useful information from medical images. Many applications would take great advantage by using scientific workflow technology due to its design, rapid implementation and reuse. However this technology requires a distributed computing infrastructure (such as Grid or Cloud) to be executed efficiently. One of the most used workflow manager for medical image processing is the LONI pipeline (LP), a graphical workbench developed by the Laboratory of Neuro Imaging (http://pipeline.loni.usc.edu). In this article we present a general approach to submit and monitor workflows on distributed infrastructures using LONI Pipeline, including European Grid Infrastructure (EGI) and Torque-based batch farm. In this paper we implemented a complete segmentation pipeline in brain magnetic resonance imaging (MRI). It requires time-consuming and data-intensive processing and for which reducing the computing time is crucial to meet clinical practice constraints. The developed approach is based on web services and can be used for any medical imaging application
Focal Spot, Spring 1998
https://digitalcommons.wustl.edu/focal_spot_archives/1078/thumbnail.jp
Development of an electronic medical report delivery system to 3G GSM mobile (cellular) phones for a medical imaging department
Author name used in this publication: Dagan FengAuthor name used in this publication: Michael FulhamRefereed conference paper2007-2008 > Academic research: refereed > Refereed conference paperVersion of RecordPublishe
Focal Spot, Spring 1999
https://digitalcommons.wustl.edu/focal_spot_archives/1081/thumbnail.jp
Aerospace Medicine and Biology: A continuing bibliography with indexes (supplement 290)
This bibliography lists 125 reports, articles and other documents introduced into the NASA scientific and technical information system in October 1986
- …